cd3662fc8c6a4e2851cdfcd81513611d3d9b7467,skrebate/scoring_utils.py,,SURF_compute_scores,#,445

Before Change

def SURF_compute_scores(inst, attr, nan_entries, num_attributes, mcmap, NN, headers, class_type, X, y, labels_std, data_type, weight_flag=0, weights=None):
     Unique scoring procedure for SURF algorithm. Scoring based on nearest neighbors within defined radius of current target instance. 
    scores = np.zeros(num_attributes)
    if weight_flag == 2:
        if len(NN) <= 0:
            return scores
        for feature_num in range(num_attributes):
            scores[feature_num] += weights[feature_num]*compute_score(attr, mcmap, NN, feature_num, inst,
                                                                      nan_entries, headers, class_type, X, y, labels_std, data_type)
    else:
        if len(NN) <= 0:
            return scores
        for feature_num in range(num_attributes):
            scores[feature_num] += compute_score(attr, mcmap, NN, feature_num, inst,
                                                 nan_entries, headers, class_type, X, y, labels_std, data_type)
    return scores


def SURFstar_compute_scores(inst, attr, nan_entries, num_attributes, mcmap, NN_near, NN_far, headers, class_type, X, y, labels_std, data_type, weight_flag=0, weights=None):

After Change

    scores = np.zeros(num_attributes)
    if len(NN) <= 0:
        return scores
    for feature_num in range(num_attributes):
        scores[feature_num] += compute_score(attr, mcmap, NN, feature_num, inst,
                                             nan_entries, headers, class_type, X, y, labels_std, data_type)
    return scores


def SURFstar_compute_scores(inst, attr, nan_entries, num_attributes, mcmap, NN_near, NN_far, headers, class_type, X, y, labels_std, data_type):

Instances